NEMO |
University of New South Wales |
true |
true |
GNU General Public License version 3.0 (GPL-3.0) |
all |
|
true |
dispatch |
|
Australia |
Optimization Simulation |
Optimisations are carried out using a single-objective evaluation function (with penalties). The search space (of generator capacities) is searched using the CMA-ES algorithm. |
minimise average cost of electricity |
|
Python |
transmission |
|
Hour |
NEMO (SEI) |
Stockholm Environment Institute |
true |
false |
Apache License 2.0 (Apache-2.0) |
|
Full energy system optimization flexible geographic and sectoral scope |
true |
dispatch investment |
|
All |
Optimization |
Constrained cost optimization with perfect foresight |
Minimize total discounted costs |
Deterministic but can readily be applied in Monte Carlo analyses |
Julia |
transmission distribution DC load flow net transfer capacities |
SQLite |
Hour |
OMEGAlpes |
G2Elab |
true |
false |
Apache License 2.0 (Apache-2.0) |
some |
Production consumption conversion storage |
true |
|
|
|
Optimization |
|
|
|
OMEGAlpes, PuLP |
|
|
|
OSeMOSYS |
KTH Royal Institute of Technology |
true |
true |
Apache License 2.0 (Apache-2.0) |
all |
|
true |
investment |
|
Africa (all countries), Sweden, Baltic States, Nicaragua, Bolivia, South America, EU-27+3 |
Optimization |
Linear optimisation (with an option of mixed-integer programming) |
Minimise total discounted cost of system |
|
GNU MathProg |
transmission distribution |
Python |
Day |
Oemof |
Reiner Lemoine Institut / ZNES Flensburg |
true |
true |
GNU General Public License version 3.0 (GPL-3.0) |
some |
Energy Modelling Framework |
true |
dispatch investment |
|
Depends on user |
Optimization Simulation |
https://oemof.org/libraries/ |
costs, emissions |
Deterministic |
Python, Pyomo, Coin-OR |
transmission distribution net transfer capacities DC load flow |
PostgreSQL, PostGIS |
Hour |
OnSSET |
KTH Royal Institute of Technology |
true |
false |
MIT license (MIT) |
|
|
true |
|
|
Sub-Saharan Africa, developing Asia, Latin America |
Optimization |
|
Cost minimization |
|
Python |
|
Python |
Multi year |
OpenTUMFlex |
Technical University of Munich |
true |
false |
GNU General Public License version 3.0 (GPL-3.0) |
some |
Energy System Model urban energy systems load shifting optimisation Local energy systems |
true |
|
|
User dependent |
Optimization Simulation |
|
Cost optimal optimization and flexibility calculation |
|
Python (Pyomo) |
distribution |
|
15 Minute |
PLEXOS Open EU |
University College Cork |
false |
true |
|
all |
Market Model |
true |
dispatch |
|
North West Europe |
Optimization |
Least Cost Optimization, Can be run in MIP or linear relaxed mode |
Minimize total Generation cost |
None |
PLEXOS |
net transfer capacities |
MS Excel |
Hour |
POMATO |
TU Berlin |
true |
false |
GNU Library or "Lesser" General Public License version 3.0 (LGPL-3.0) |
some |
Network-constrained Unit Commitment and Economic Dispatch |
true |
dispatch |
|
User-dependent |
Optimization |
Linear Economic Dispatch. Linear Optimal Power Flow. Linear Security Constrained Optimal Power Flow |
Cost minimization |
Chance Constrained |
Julia/JuMP |
transmission DC load flow net transfer capacities |
Python |
Hour |
Pandapipes |
Fraunhofer IEE, Uni Kassel |
true |
true |
MIT license (MIT) |
|
|
false |
|
|
|
Simulation |
|
|
|
Python |
distribution |
|
|
Pandapower |
|
true |
false |
BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) |
some |
Transmission Network Model |
true |
|
|
|
Simulation |
|
|
|
Python |
transmission distribution |
Pandas |
|
PowNet |
Singapore University of Technology and Design |
true |
false |
MIT license (MIT) |
all |
Network-constrained Unit Commitment and Economic Dispatch |
true |
dispatch |
|
Laos, Cambodia, Thailand, any user-defined country or region |
Optimization Simulation |
Mixed Integer Linear Program (MILP), DC Power Flow, Unit Commitment, Economic Dispatch |
Cost minimization |
Sensitivity analysis |
Python (Pyomo) |
transmission distribution DC load flow |
Python |
Hour |
PowerMatcher |
Flexiblepower Alliance Network |
true |
false |
Apache License 2.0 (Apache-2.0) |
|
|
true |
|
|
|
|
|
|
|
Java |
|
|
|
PowerSimulations.jl |
NREL |
true |
false |
BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) |
|
quasii-static sequential unit-commitment and economic dispatch problems |
true |
dispatch |
|
Any |
Optimization |
Principal application is sequential quasi-static system optimization problems (production cost modeling). |
Least Cost |
scenario analysis |
Julia |
transmission AC load flow DC load flow net transfer capacities |
Julia |
Second |
PowerSimulationsDynamics.jl |
NREL |
true |
false |
BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) |
|
Dynamic system simulation model library |
true |
|
|
|
Simulation |
PowerSimulationsDynamics.jl enables transient stability analysis of power systems through differential-algebraic equations and with forward differentiation to enable small-signal stability analysis. |
N/A |
scenario analysis |
Julia |
transmission AC load flow |
Julia |
Less than second |
PowerSystems.jl |
NREL |
true |
false |
BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) |
|
Optimization Simulation |
true |
dispatch |
|
Any |
Simulation |
PowerSystems.jl includes basic power flow and network matrix calculation capabilities. |
|
scenario analysis |
Julia |
transmission AC load flow DC load flow net transfer capacities |
Julia |
Less than second |
Pvlib python |
|
true |
false |
BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) |
some |
|
true |
|
|
|
Simulation |
|
|
|
Python |
|
NumPy, Pandas |
|
PyLESA |
University of Strathclyde |
true |
false |
MIT license (MIT) |
some |
Local energy systems |
true |
dispatch |
|
|
Simulation |
|
Minimization of operational costs |
perfect foresight |
Python |
AC load flow DC load flow |
Python |
Hour |
PyPSA |
FIAS |
true |
false |
GNU General Public License version 3.0 (GPL-3.0) |
all |
Energy System Model |
true |
dispatch investment |
|
Europe, China, South Africa |
Optimization Simulation |
Non-linear power flow; linear optimal power flow / investment optimisation |
Cost minimization |
Not explicitly covered, but stochastic optimisation possible |
Python, Pyomo |
transmission distribution AC load flow DC load flow net transfer capacities |
Pandas |
Hour |
QuaSi - GenSim |
Siz energieplus |
true |
false |
MIT license (MIT) |
all |
building energy demand |
true |
|
|
All |
Simulation |
EnergyPlus is used to perform a thermal building simulation |
|
|
EnergyPlus, OpenStudio, MS Excel, Ruby |
|
MS Excel |
15 Minute |
QuaSi - ReSiE |
Siz energieplus |
true |
false |
MIT license (MIT) |
all |
multi energy systems in urban scale |
true |
dispatch investment |
|
Depends on user |
Simulation Other |
rule-based algorithms, system dynamics |
energy balances |
sensitivity analysis |
Julia |
transmission distribution |
Julia |
15 Minute |
QuaSi - SoDeLe |
Siz energieplus |
true |
false |
MIT license (MIT) |
all |
PV energy production |
true |
|
|
All |
Simulation |
physics-based with efficiency curves from CEC |
|
|
Python |
|
Python, MS Excel |
Hour |
REopt |
The National Renewable Energy Laboratory |
true |
false |
BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) |
some |
Energy System Model |
true |
dispatch investment |
|
World |
Optimization |
Mixed Integer Linear Program |
Minimize Lifecycle Cost |
|
Julia/JuMP |
|
Python |
Hour |
Region4FLEX |
DLR Institute of Networked Energy Systems |
true |
false |
Apache License 2.0 (Apache-2.0) |
all |
load shifting optimisation |
false |
|
|
Germany |
Optimization |
|
|
|
Python |
transmission |
PostgreSQL |
15 Minute |
Renpass |
ZNES Flensburg |
true |
true |
GNU General Public License version 3.0 (GPL-3.0) |
all |
Electricity System Model / Regional Dispatch Model / Transshipment Model |
true |
dispatch |
|
Poland, Lithuania, Latvia, Estonia, Finland, Sweden, Denmark, Norway, the Netherlands, Belgium, Luxembourg, France, Switzerland, Austria, the Czech Republic, Germany |
Optimization Simulation |
Minimization of costs for each time step (optimization) within the limits of a given infrastructure (simulation) |
economic costs |
perfect foresight |
R |
net transfer capacities |
MySQL / R / RMySQL |
Hour |
SIREN |
Sustainable Energy Now Inc |
true |
false |
Affero General Public License v3 (AGPL-3.0) |
some |
Electricity System Model |
true |
dispatch investment |
|
|
Simulation Other |
Uses NREL SAM models to estimate hourly renewable generation for a range/number of renewable energy stations |
Match generation to demand and minimise cost |
|
Python, NREL SAM |
|
Python |
Hour |
SMS++ |
Dipartimento di Informatica, Università di Pisa |
true |
false |
GNU Library or "Lesser" General Public License version 3.0 (LGPL-3.0) |
some |
in princople all short- to long-term optimization |
true |
dispatch investment |
|
Any |
Optimization |
in principle any optimization model, particular emphasis on decomposition approaches |
in principle any, currently cost minimization |
in principle any, currently scenarios |
SMS++ |
transmission distribution DC load flow net transfer capacities |
hand-coded C++ |
Multi year |
SciGRID gas |
DLR Institute of Networked Energy Systems |
true |
false |
Creative Commons Attribution 4.0 (CC-BY-4.0) |
all |
European Gas Transmission Network Model and Data (input and output) |
true |
|
|
Europe |
Other Simulation |
|
|
|
GeoJSON & CSV |
|
|
|
SciGRID power |
DLR Institute of Networked Energy Systems |
true |
true |
Apache License 2.0 (Apache-2.0) |
all |
Transmission Network Model |
true |
|
|
Europe and Germany (any other EU country also possible) |
Simulation |
We consider a topological graph (V,L) as a mathematical structure that consists of a set V of vertices and a set L of nonempty subsets of V called links. |
|
|
Python, PostgreSQL |
transmission |
Python, PostgreSQL, Osmosis, osm2pgsql |
|
SimSEE |
Institute of Electrical Engineering |
true |
false |
GNU General Public License version 3.0 (GPL-3.0) |
some |
Optimal energy dispatch |
true |
dispatch investment |
|
|
Optimization Simulation |
Optimal Stochastic Dynamic Programming solver for computation of the operational Policy and a Monte Carlo style simulator of the system using the computed Policy |
minimization of the future operational cost. |
stochastic, hydro inflows, wind velocity, solar radiation, temerature an Demand. |
freepascal |
net transfer capacities |
freepascal |
Hour |
SimSES |
Technical University of Munich |
true |
false |
BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) |
all |
Electrical energy storage system |
true |
dispatch |
|
World |
Simulation |
Power flow and state of charge calculation based on time series profiles |
|
|
Python |
|
Python |
Minute |
SpineOpt.jl |
|
true |
false |
GNU Library or "Lesser" General Public License version 3.0 (LGPL-3.0) |
some |
Framework |
true |
dispatch investment |
|
|
Optimization |
Linear programming or mixed integer linear programming |
Cost minimization |
Deterministic, perfect foresight, myopic, stochastic. |
Julia/JuMP |
transmission DC load flow net transfer capacities |
Python, Spine Toolbox |
Hour |
StELMOD |
DIW Berlin |
true |
false |
MIT license (MIT) |
|
Optimization |
true |
dispatch |
|
Europe (particular focus on Germany) |
Optimization |
Mixed integer linear optimization for separate electricity markets (dayahead, intraday, congestion management) linked by a rolling planning procedure |
Minimization of total generation cost |
deterministic, stochastic |
GAMS |
transmission DC load flow net transfer capacities |
MS Excel |
Hour |
Switch |
Environmental Defense Fund |
true |
false |
Apache License 2.0 (Apache-2.0) |
all |
Power system capacity expansion energy system |
true |
dispatch investment |
|
|
Optimization |
intertemporal mathematical optimization |
total cost or consumer surplus, including environmental adders |
stochastic treatment of hourly renewable variability; allocation of reserves for sub-hourly variability; scenarios or progressive hedging for uncertain annual weather or fuel or equipment costs |
Python, Pyomo |
transmission distribution AC load flow DC load flow net transfer capacities |
Python, any user-selected software |
Hour |
System Advisor Model (SAM) |
National Renewable Energy Laboratory |
true |
false |
BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) |
|
International renewble energy project modeling |
true |
dispatch |
|
|
Simulation |
Time series simulation of power system performance coupled with annual pro forma cash flow calculations. |
time series power generation, installation cost, annual operating and financial cost |
stochastic, deterministic |
C++, WxWidgets |
|
|
Minute |
TIMES |
IEA-ETSAP |
true |
false |
GNU General Public License version 3.0 (GPL-3.0) |
|
Local National Regional Global models developed using TIMES |
true |
dispatch investment |
|
Local, National, Regional, Global models |
Optimization |
Partial equilibrium, least cost optimisation, with MIP, NLP options. Perfect foresight and myopic options. |
Total discounted system cost minimisation |
Deterministic, perfect foresight, myopic, stochastic. |
GAMS |
transmission DC load flow net transfer capacities |
EXCEL, VEDA, ANSWER |
Hour |
TIMES Évora |
CENSE - NOVA University Lisbon |
false |
true |
|
|
Energy supply and demand |
true |
|
|
Évora (Portugal) |
Optimization |
|
Minimise total discounted cost of the energy system |
|
GAMS |
|
|
Seasonal |
TIMES-PT |
CENSE - NOVA University Lisbon |
false |
true |
|
|
Energy supply and demand |
true |
|
|
Portugal |
Optimization |
|
Minimise total discounted cost of the energy system |
|
GAMS |
transmission distribution |
|
Seasonal |
Temoa |
NC State University |
true |
false |
GNU General Public License version 2.0 (GPL-2.0) |
all |
energy system optimization model |
true |
investment |
|
U.S., currently |
Optimization |
The model objective is to minimize the present cost of energy supply by deploying and utilizing energy technologies and commodities over time to meet a set of exogenously specified end-use demands. |
Cost minimization |
stochastic optimization, moeling-to-generate alternatives |
Python (Pyomo) |
|
SQLite |
Multi year |
TransiEnt |
Hamburg University of Technology |
true |
false |
|
some |
Dynamic system simulation model library |
true |
|
|
Hamburg / Germany |
Simulation |
Models in the library are based on differential algebraic equations and are solved using a variable step solver. By using the object oriented Modelica language the library allows an investigation of different timescales and levels of physical detail. |
|
Prediction errors can be introduced by (filtered) white noise timeseries to see changes in control behaviour |
Modelica |
transmission distribution net transfer capacities |
Dymola |
Second |
URBS |
TUM EI ENS |
true |
true |
GNU General Public License version 3.0 (GPL-3.0) |
some |
Energy Modelling Framework |
true |
dispatch investment |
|
User-dependent |
Optimization |
Linear optimization model of a user-defined reference energy system. |
Minimise total discounted cost of system |
None |
Python (Pyomo) |
transmission net transfer capacities |
Python (pandas et al) |
Hour |
USENSYS |
Environmental Defense Fund |
true |
false |
Affero General Public License v3 (AGPL-3.0) |
all |
Capacity expansion Reference Energy System |
true |
investment |
|
US 48 lower states & DC |
Optimization |
Linear programming |
Cost minimization |
Deterministic |
R/energyRt |
transmission |
R |
Hour |